pytest-benchmark
pydantic-core
| pytest-benchmark | pydantic-core | |
|---|---|---|
| 2 | 18 | |
| 1,200 | 1,283 | |
| - | 2.2% | |
| 6.0 | 9.6 | |
| about 2 months ago | 11 days ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pytest-benchmark
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Pinpoint performance regressions with CI-Integrated differential profiling
pytest-benchmark
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Investigating Pydantic v2's Bold Performance Claims
To test this, we will setup some benchmarks using pytest-benchmark, some sample data with a simple schema, and compare results between Python's dataclass, Pydantic v1, and v2.
pydantic-core
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Is there a pydantic.BaseSettings equivalent in rust?
Funny that you ask... https://github.com/pydantic/pydantic-core Unfortunately it seems that the functionality you ask for is not (yet) part of this ...
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Investigating Pydantic v2's Bold Performance Claims
I encourage you to checkout the official benchmarks for more realistic and detailed examples, and, as always, YMMV.
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Pydantic V2 leverages Rust's Superpowers [video]
> to also be constrained by a separate set of data types which are legal in rust.
This isn't really how writing rust/python iterop works. You tend to have opaque handles you call python methods on. Here's a decent example I found skimming the code.
https://github.com/pydantic/pydantic-core/blob/main/src/inpu...
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Pydantic vs Protobuf vs Namedtuples vs Dataclasses
Thanks for pointing out to that, I did not know about it. Also attaching repo in case someone would be interested as well - https://github.com/pydantic/pydantic-core
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Introducing CodSpeed: Continuous Performance Measurement
pydantic-core: The core validation logic for pydantic, a Python data parsing and validation library.
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Show HN: Python framework is faster than Golang Fiber
pydandic-core [0] will hopefully solve this issue (written in Rust)
[0] -- https://github.com/pydantic/pydantic-core
- Scala or Rust? which one will rule in future?
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Rust for Data Engineering—what's the hype about? 🦀
LinkedIn influencers are weird lol. Rust v Python is apples and oranges. Rust would be glued together by python just like it does with C/C++ and Java/Spark today. We’re already seeing some packages go this direction, like pydantic v2 is rewriting its core validation in rust.
- Python file structure with Rust extensions
- Pydantic 2 rewritten in Rust was merged
What are some alternatives?
pytest-codspeed - Pytest plugin to create CodSpeed benchmarks
aiohttp-apispec - Build and document REST APIs with aiohttp and apispec
action - Github Actions for running CodSpeed in your CI
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
cloud_benchmarker - Cloud Benchmarker automates performance testing of cloud instances, offering insightful charts and tracking over time.
pymartini - A Cython port of Martini for fast RTIN terrain mesh generation
pyperf - Toolkit to run Python benchmarks
koda-validate - Typesafe, Composable Validation
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
modin - Modin: Scale your Pandas workflows by changing a single line of code
asv - Airspeed Velocity: A simple Python benchmarking tool with web-based reporting
typedload - Python library to load dynamically typed data into statically typed data structures